Mucus composition and bacterial communities associated with the tissue and skeleton of three scleractinian corals maintained under culture conditions
Bibliographic record
Abstract
Corals live in close association with bacterial communities, but the nature of the relationship is still poorly understood. In this study, three scleractinian coral species, Galaxea fascicularis, Pavona cactus and Turbinaria reniformis were incubated under different laboratory conditions, and the composition of the bacterial community associated with their tissue or skeleton was compared between species or between species and seawater using denaturing gradient gel electrophoresis (DGGE). The amount of dissolved organic carbon (DOC) excreted and the mucus glycoconjugate composition were also determined for each species. The aim of the study was to assess if the bacterial community composition was species-specific or linked either to the seawater composition, or to the quality and quantity of carbon released by each coral. Results obtained showed that DOC release was significantly different ( P < 0.0001) for the three species, with the highest excretion rate for G. fascicularis . Also, the mucus of G. fascicularis and P. cactus mainly contained galactose and glucose whereas the mucus of T. reniformis contained more glucose and xylose. Cluster analyses of microbial community composition showed that the bacterial community was species-specific in the coral tissue but not in the skeleton, in all conditions. It remained specific when corals were incubated in the same or in different aquaria, and under different seawater renewal rates. Since DOC release rates and bacterial composition were both different according to the coral species considered, a link might be suggested between the two parameters. Sequencing of DGGE bands indicated that some bacterial phylotypes were consistently retrieved in all samples of a given species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".